AI, Analytics, And Conservation: The Nature Conservancy's Data Transformation Story

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[00:00:28] So turn your Lakehouse investment into real business outcomes with Denodo. So please visit Denodo.com How does better data actually help protect the planet? It's a question that doesn't get asked often enough, especially in conversations around AI and analytics. But it sits at the heart of today's episode.

[00:00:51] Because behind every conservation effort out there, every protected habitat and every environmental initiative, these are all areas that you don't associate with technology. But behind the scenes, there is both tech and a financial engine that needs to work efficiently to make it all possible. So at SAS Innovate, I sat down with John Blackwell, Director of Strategic Analytics at the Nature Conservancy.

[00:01:17] And they are one of the largest conservation organizations in the world, operating across more than 80 countries and raising over a billion dollars annually to support its mission. So today I want to learn more about how analytics and technology play a critical role in maximizing the impact of every donation. Whether that be improving donor retention, increasing giving or building a complete view of supporter behavior across every channel.

[00:01:46] And my guests will share how data is helping the organization work smarter, reduce waste and ultimately direct more funding towards conservation efforts. I will also discuss that shift from fragmented systems to what a unified data strategy looks like, how personalization works in a non-profit context. And do so without losing authenticity.

[00:02:09] And understand why small incremental improvements across multiple areas can actually compound into significant results over time. Ultimately, it's a conversation that connects technology to something much bigger than just business outcomes. We're talking about real world impact for nature, communities and future generations. But enough from me. Let me introduce you to my guests now. So thank you for joining me here.

[00:02:39] For everyone listening, can you tell them a little about who you are and what you do? Yeah. So I'm John Blackwell and I'm the director of the strategic analytics team at The Nature Conservancy. And yeah, what my job is to basically help the organization raise as much money as efficiently as possible through using analytics. I understand that you're protecting land and water across 83 different countries, but your role sits more the intersection of analytics and fundraising.

[00:03:06] So for listeners unfamiliar with that world, how does better data directly translate into better outcomes for conservation? Because it's probably something people don't think about. Yeah. I mean, I think you cited one of our 2030 goals and they're very ambitious. And so we are the biggest conservation organization in the world. And I think maybe what people don't wouldn't necessarily understand is how expensive that is, how much it costs to do some of those things that you that you say.

[00:03:33] So, yeah, I mean, we we raise over a billion dollars a year and we have to obviously spend as little money to do that as possible so that, you know, the money can go to support conservation. And yeah, the way of doing the way we do that is through is through analytics. And some of the standout results that I was reading about before you joined me today was improving donor retention by 10 percent and increasing year over year giving by 30 percent.

[00:04:02] So what were the biggest changes behind what some of the biggest changes behind those results? And what did the organization learn along the way? Because there's such a big focus on ROI of every tech project. There's some pretty big ROI there, isn't there? Yeah, yeah. I so I mean, there's it's hard to pick just one thing that would go into that. But I mean, I think sort of the thing that a lot of organizations are always going to struggle with is acquiring new donors because that's expensive.

[00:04:30] You know, it's always going to cost money. You're never you're always going to spend more money on acquiring a new donor than they're going to give you in that first year. So what you need to be sure of or assures what you need to be sure of is is that those people will will generate net revenue for you over time. And so one of the one of the things that we've been able to do is really sort of hone in on those people who will provide the most value to the organization.

[00:04:58] And so, you know, not not waste any resources on spending money on people who can't necessarily afford to give very much or could potentially only give you one ten dollar gift and, you know, wouldn't be able to give you again. We're really able to focus on those people with the means and and sort of the propensity to want to support conservation.

[00:05:18] And if we look at a before and after picture, I believe working before you started working with SAS donor and marketing data was often siloed across channels like email, phone, email and digital ads. What problems did that create for your team and how important was it building that true 360 degree view of every support? Yeah, it was a it was a real it was a real headache because we we we had we know we had one system for our direct mail.

[00:05:43] We had one system for email and, you know, another thing for telemarketing. And then we also worked with some outside vendors as well to execute on on any of those channels. And so, you know, if you wanted to take into account like in one channel that somebody had been like opening emails, it was just very difficult to do. So. So, yeah, I mean, one of the first projects that we so what we realized is that, you know, we needed to be able to bring the data into one.

[00:06:13] Let me actually back up a little bit. So one of the complications with the old with the old system is that even as I was building up the analytics team and the analytics was becoming more sophisticated, we just hit that sort of limits, that sort of execution limit like we couldn't execute on any of the things. And so sometimes we'd actually develop models, but we'd be working with external partners and they wouldn't actually be able to implement them. So they wouldn't do any good.

[00:06:39] So implementing the SAS CI 360, what that allowed to do, what that allowed us to do was have end to end control over everything. So from developing the analytics to the execution as well. And that was really the, you know, that that that was really the initial boost to us is that we weren't limited by the complexity of of the logistics of working with multiple partners and multiple systems anymore.

[00:07:07] And when I was doing a little research on you guys, I was reading how a relatively small group of major donors drive a large percentage of your total fundraising while millions of smaller donors. They also play an equally important, massive role too. So how does analytics help you balance both ends of that spectrum without losing sight of either? Yeah. So the membership department, I mean, they're for the most part, they're in charge of, you know, bringing on those low dollar donors.

[00:07:32] But what a lot of people don't realize is that for those people who make very big gifts, they often, the majority of them come from the membership pool. So we will, we will acquire somebody and, you know, maybe they're giving to us $50, $100 a year, and they're just getting a direct mail piece from us. They're getting, they're getting email from us, but they would give a lot more if they had that sort of one-on-one cultivation from a fundraiser.

[00:07:59] And so, you know, you really can't look at doing one thing or the other. We have to bring in as many, as many valuable donors as possible because we know that that's going to be the pool that ultimately makes up that, you know, the, you know, those major, major donors in the future.

[00:08:14] And so, you know, one of the, you know, in addition to making sure that we're bringing on like good membership donors, like one of our key focus areas right now is just being able to better predict, better find those prospects within that membership pool who, you know, who have the capacity to give a lot more were they to receive a more personalized treatment. You mentioned personalized there.

[00:08:38] I mean, personalization is a major focus for modern marketing now, but in a nonprofit environment, how do you use personalization to strengthen those supporter relationships without making it feel transactional or overly commercial? I mean, there's a few things. There's a few things that we're doing. I mean, one of the things that I guess sort of surprised me is that, you know, we have some, you know, we have some donors who like they'll be on our email file. They'll be getting emails from us.

[00:09:07] They're also in our direct mail file and getting direct mail from us. And they will never, ever sort of respond to a direct mail piece directly. They will only ever give it to us online. And so, you know, the initial thought is that we can just cut out direct mail from that group. But what we actually found is that so many of our donors actually are triggered to give through receiving the direct mail. They just don't write checks anymore because almost nobody does.

[00:09:32] And so, you know, we've been able to identify, we've been able to better identify sort of what, and there, of course, are some people who just throw away direct mail and who only want to hear from us by email. And so, what we've been able to do is understand which portions of our file only want to hear from us online, which portions of our file want to hear from us through both channels, which portions of our file we need to reach through telemarketing. So, being able to reach them in the right channel certainly does help.

[00:10:06] Thank you. Thank you.

[00:10:59] Thank you.

[00:11:30] Thank you. Thank you.

[00:12:29] Thank you. Thank you.

[00:13:05] Thank you.

[00:13:37] Thank you. And I think we've set a record because this is a tech podcast. We've lasted 15 minutes without mentioning AI, but we've got to bring it in. When you look at advanced automation and AI, including trigger-based communications, AI-generated recommendations, where do you see the biggest opportunity for nonprofits to work smarter without losing that human connection that donors expect?

[00:14:28] Yeah. in addition to that, just sort of like the feature selection and performance tuning of the actual models is all done through AI. So like, I mean, those are all very straightforward things. But to really get to your question, we have been more hesitant to use AI in terms of like the content generation, just because, you know, we do definitely have a voice and we're worried that,

[00:14:57] you know, injecting too much AI into that, you know, we could lose our voice. And, you know, all of a sudden, we could see declining results. We are experimenting with that, but we're doing it extremely cautiously because we're worried about just that. And you mentioned you're here at SAS Innovate and you've done a presentation. So what was all that about? What have you been talking about? And what have you been doing during your time here?

[00:15:24] Yeah. Well, so I mean, one of the one of the big key themes of my presentation today is, you know, there is a lot that we're hearing about a lot of like, like big companies you'll hear about, like just very cool projects that they're doing, like with digital twins, and just, you know, all of these things that just require a big investment, but they're big, big projects using sort of like, you know, cutting it cutting edge AI technology. And I think maybe a blind spot for a lot of

[00:15:50] organizations, you know, not just nonprofits, but a lot of organizations here, it's just not realizing how like the compounding effects of like small changes to lots of things. So if you can make all of your models just a little bit better with AI, and you can create them quicker, and you can deploy them quicker, and those are all very easy things to do that virtually anybody can do, you know, that that leads to the compounding effect and leads to sort of some of the growth that you referenced

[00:16:17] earlier on in this conversation. And what about all the announcements here? Anything stand out to you? Anything that inspired you that you thought, okay, that could kind of work for us? Anything really stand out to you there? Yeah, I mean, the things that in one of the in the opening presentation, actually, here, I mean, they were talking about the SAS Data Maker project, product and synthetic data generation. And so that's one of the things that we're, we're most excited

[00:16:42] about is synthetic data, helping you to predict rare events. And so like the obvious use case for that for us is what I was talking to you about earlier in terms of identifying those needles in the haystack, those people who will like who are capable of giving those multimillion dollar gifts, like in our general membership population. And so, you know, through through the use of synthetic data, we think we can tweak those models further. So that's something that we're really excited about.

[00:17:10] And at the heart of everything we're talking about, it has to solve the problem of fundraising success supports conservation outcomes. So when you step back from all that and all the noise and all the technology, how does better analytics help turn marketing improvements into a very real world impact for nature, communities and indeed future generations? Because that's the power here. Yeah, it is. And I mean, if you if anybody listening to this just thinks about it,

[00:17:37] like if you're giving your money to an organization, I mean, you you want most of that. I mean, I think people do realize that some of the money that you give to a nonprofit, you know, it goes to sort of program, or sorry, it goes to just sort of like the overhead associated with with with raising that money. So like, the reason why one of the reasons why we have been able to grow, the way we have been able to grow is because of the amount of the money that we raise

[00:18:06] that goes directly towards or supports our programs. And like the way we can the way we can make that more efficient when we can sort of increase the percentage of every single dollar that goes towards conservation, the more people are likely to give to us. So it's kind of this that this sort of loop, you know, that feeds on itself, the better we get at doing this, the more efficient we become, and the more people are likely to want to give to us because, I mean, especially before people give big gifts, but even before they give small gifts,

[00:18:34] they will look at some of the different, you know, charity sites that rate the effectiveness of charities. And so it is critically important to us that we're not, you know, we're not wasting any money whatsoever. I think that's a powerful moment to end on. But for anybody listening, whether they be a high profile donor, or maybe somebody another nonprofit looking to learn from your story, I'll include a link to your LinkedIn page. But is it anywhere else you'd like to send everyone, maybe the website, any or anything else that you'd like me to point everyone?

[00:19:04] Well, hey, I'll tell them to sign up for our emails. And so you can see the end results of our analytics in your email box. And yeah, give us a donation if you if you can. Awesome. Well, I'll put links to everything there. I urge people to check those out. But just thank you for joining me today. Thank you. What really stood out to me in this conversation is just how closely efficiency and impact are connected. In a nonprofit like this, improving analytics is not about increasing

[00:19:31] profit margins. It's about ensuring that more of every single dollar raised goes directly towards protecting land, water and ecosystems all around the world. And for me, this changes how you think about ROI entirely. Whether it be identifying the right donors or personalizing engagement without losing trust or authenticity to using AI carefully in areas like model building while

[00:19:57] protecting an organization's voice. Every decision is made with this balance in mind. Technology is there to support the mission, not overshadow it. There's also an important lesson here for any organization. And that is you don't need massive transformation projects to see results. As John pointed out today, small improvements across multiple areas, better models, faster deployment, smarter targeting, all these things compound into very meaningful growth over time.

[00:20:26] So as always, I'll include links to show to the show notes so you can learn more about the work that's happening there and connect with John. But I'd love to hear your perspective. Are you working in a nonprofit? How are you measuring the real world impact of your data and AI investments? And are they making a difference beyond the balance sheet? Let me know. techtalksnetwork.com. We have 4,000 interviews there, lots of ways of working with me, but

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